Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome

Ken Mills, A. Kohlmann, P.M. Williams, L. Wieczorek, W.M. Liu, R. Li, W. Wei, D.T. Bowen, H. Loeffler, J.M. Hernandez, W.K. Hofmann, T. Haferlach

Research output: Contribution to journalArticlepeer-review

115 Citations (Scopus)

Abstract

The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or
Original languageEnglish
Pages (from-to)1063-1072
Number of pages10
JournalBlood
Volume114
Issue number5
DOIs
Publication statusPublished - 2009

ASJC Scopus subject areas

  • Hematology
  • Biochemistry
  • Cell Biology
  • Immunology

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